Investment ML Analyst

Bracebridge Capital

Boston (MA)

On-site

USD 110,000 - 145,000

Full time

14 days+

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Job summary

Bracebridge Capital in Boston’s Back Bay is seeking a Machine Learning Analyst to join the growing data analytics and ML team. You will contribute to developing ML systems to answer open-ended investment questions and support portfolio management decisions.

The role spans research, software engineering and ML, with collaboration across traders and researchers. Candidates should have solid Python programming foundations and comfort turning qualitative ideas into quantitative tools; prior finance

Qualifications

  • 0-2 years of experience through internships, undergrad research, or similar projects.
  • Proficiency in Python and familiarity with the Python data science stack.
  • Experience analyzing data from multiple sources and formats.
  • Solid grounding in ML and statistical modeling, including evaluation design.
  • Ability to scope and execute open-ended technical projects independently.
  • Interest in financial markets and strong written/verbal communication skills.

Responsibilities

  • Collaborate with ML team, portfolio managers and researchers to translate investment questions into analytical ML problems.
  • Develop and evaluate data-driven ML and quantitative models, including simulation-based approaches.
  • Contribute to maintaining existing models and analytic tools in production.
  • Over time, take ownership of features, components and projects.
  • Document and communicate methods, results and limitations to researchers and trading professionals.
  • Stay current with ML and AI techniques as they pertain to finance and investing.

Skills

Strong communication
Independent project execution
Interest in finance

Tools

Python
NumPy
Pandas
SciPy
scikit-learn

Job description

Bracebridge Capital in Boston’s Back Bay is seeking a Machine Learning Analyst to join the growing data analytics and ML team. You will contribute to developing ML systems to answer open-ended investment questions and support portfolio management decisions.

The role spans research, software engineering and ML, with collaboration across traders and researchers. Candidates should have solid Python programming foundations and comfort turning qualitative ideas into quantitative tools; prior finance

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